David Axelrod - Professor

Cell and molecular oncology. breast cancer

The focus of this laboratory is on the heterogeneity and instability of cancer cells. Our goal is to improve cancer diagnosis. prognosis and to guide therapy. Methods of molecular biology. cell biology. computer simulation and mathematical modeling are being used.

Currently. we are studying the heterogeneity and progression of human breast cancers. Clinical specimens are being analyzed. as well as clonal populations of established cell lines and short term cultures of cells from fresh biopsy specimens. Computer-aided image analysis allows us to measure. on a single cell basis. the expression of specific genes coding for oncoproteins. tumor suppressor proteins. and hormone receptors; as well as quantification of DNA densitometry. nuclear morphometry and chromatin texture. Multivariate analysis of image cytometry features is being used to derive discriminant functions to aid in the differential diagnosis of human breast tumors and normal tissues. Molecular data are being correlated with the growth and regression of clonal populations of tumor cells.

In addition. mathematical models that incorporate stochastic and deterministic aspects of gene expression. cell division. cell death and inheritance of cell cycle times. are being analyzed by computer simulation and theoretical results are being compared with experimental observations. The regulation of tumor cell proliferation by signal transduction pathways is being studied with computer models that use cellular automata to describe the biochemical components of the pathways.

Selected Publications

Click here to link to Dr. Axelrod's publications in PubMed

Pienta KJ, McGregor N, Axelrod R, Axelrod DE. (2008) Ecological therapy for cancer: defining tumors using an ecosystem paradigm suggests new opportunities for novel cancer treatments. Transl Oncol. 1(4):158-64.

Axelrod, D.E., Miller, N.A., Lickely, H.L., Qian, J., Christens-Barry, W.A., Yuan, Y., Fu, Y., Chapman, J.-A.W. (2008). Effect of quantitative nuclear image features on recurrence of ductal carcinoma in situ (DCIS) of the breast. Cancer Informatics 4:99-109. Electronic Link

Chapman, J.-A.W., N.A. Miller, H.L.A. Lickley, J. Qian, W.A.?Christens-Barry, Y. Fu, Y. Yuan, and D.E. Axelrod. (2007). Ductal carcinoma in situ of the breast (DCIS) with heterogeneity of nuclear grade: Prognostic effects of quantitative nuclear assessment. BMC Cancer 2007, 7:174, doi:?10.1186/1471-2407-7-174. Electronic Link

Cardiff RD, Gregg JP, Miller JW, Axelrod DE, Borowsky AD. (2006) Histopathology as a predictive biomarker: strengths and limitations. J Nutr. 136(10):2673S-5S.

Axelrod R, Axelrod DE, Pienta KJ. (2006) Evolution of cooperation among tumor cells.
Proc Natl Acad Sci U S A. 103(36):13474-9. Review.

Alexe G, Alexe S, Axelrod DE, Bonates TO, Lozina II, Reiss M, Hammer PL. (2006) Breast cancer prognosis by combinatorial analysis of gene expression data. Breast Cancer Res. 8(4):R41.

Sontag. L. and Axelrod. D.E. (2005). Evaluation of pathways for progression of heterogeneous breast tumors. J. Theoret. Biol. 232: 179-189.

Kimmel. M. and D.E. Axelrod. (2002). Branching Processes in Biology. Springer-Verlag. NY.

Subramanian. B. and Axelrod. D.E. (2001) Progression of heterogeneous breast tumors. J. Theoret. Biol. 210: 107-119.

Chapman. J.-A.. Wolman. E.. Wolman. S.R.. Remvikos. Y.. Shackney. S.. Axelrod. D.E.. Baisch. H.. Christensen. I. J.. White. R.A.. Liebovitch. L.S.. Moore. D.H.. Walsman. F.M.. Cornelisse. C.J.. Shankey. T.V. (1998) Assessing genetic markers of tumour progression in the context of intra-tumour heterogeneity. Cytometry 31: 67-73.

Axelrod. D.E.. Gusev. Y. and Gamel. J.W. (1997) Ras-oncogene transformed and non-trans-formed cell population are each heterogeneous but respond differently to the chemotherapeutic drug cytosine arabinoside (Ara-C). Cancer Chemotherapy and Pharmacology 39: 445-451.

Staudte. R.G.. Huggins. R.M.. Zhang. J.. Axelrod. D.E. and Kimmel. M. (1997) Estimating clonal heterogeneity and interexperiment variability with the bifurcating autoregressive model for cell lineage data. Mathematical Biosciences 143: 103-121.

Axelrod. D.E.. Baggerly. K.A. and Kimmel. M. (1994) Gene amplification by unequal sister chromatid exchange: Probabilistic modeling and analysis of drug resistance data. Journal of Theoretical Biology 168: 151-159.